Research on Fast Prediction of Construction Engineering Cost Based on BP Neural Network
This article analyzes the factors affecting the cost of construction projects,selects 8 main characteristic factors including foundation type,structural type,and total number of floors of the project,and quantifies these characteristic factors to construct a feature vector that affects the cost of the project.Meanwhile,based on grey system theory,this article uses grey prediction and grey system models to process data,improving the accuracy and reliability of the data.Based on this,this article combines the BP neural network algorithm to achieve rapid prediction of construction project costs.Through repeated debugging and comparison,suitable network parameters were determined,and effective prediction of construction project cost was ultimately achieved.
BP neural networkgrey systemconstruction project costcost prediction
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